Overview

Dataset statistics

Number of variables109
Number of observations32561
Missing cells0
Missing cells (%)0.0%
Duplicate rows23
Duplicate rows (%)0.1%
Total size in memory4.9 MiB
Average record size in memory158.0 B

Variable types

Numeric6
Categorical103

Alerts

Dataset has 23 (0.1%) duplicate rowsDuplicates
age is highly correlated with marital-status_ Never-marriedHigh correlation
education-num is highly correlated with education_ Bachelors and 1 other fieldsHigh correlation
workclass_ ? is highly correlated with occupation_ ?High correlation
education_ Bachelors is highly correlated with education-numHigh correlation
education_ HS-grad is highly correlated with education-numHigh correlation
marital-status_ Married-civ-spouse is highly correlated with marital-status_ Never-married and 2 other fieldsHigh correlation
marital-status_ Never-married is highly correlated with age and 3 other fieldsHigh correlation
occupation_ ? is highly correlated with workclass_ ?High correlation
relationship_ Husband is highly correlated with marital-status_ Married-civ-spouse and 3 other fieldsHigh correlation
relationship_ Not-in-family is highly correlated with marital-status_ Married-civ-spouseHigh correlation
relationship_ Own-child is highly correlated with marital-status_ Never-marriedHigh correlation
race_ Black is highly correlated with race_ WhiteHigh correlation
race_ White is highly correlated with race_ BlackHigh correlation
sex_ Female is highly correlated with relationship_ Husband and 1 other fieldsHigh correlation
sex_ Male is highly correlated with relationship_ Husband and 1 other fieldsHigh correlation
age is highly correlated with marital-status_ Never-marriedHigh correlation
education-num is highly correlated with education_ BachelorsHigh correlation
workclass_ ? is highly correlated with occupation_ ?High correlation
education_ Bachelors is highly correlated with education-numHigh correlation
marital-status_ Married-civ-spouse is highly correlated with marital-status_ Never-married and 2 other fieldsHigh correlation
marital-status_ Never-married is highly correlated with age and 3 other fieldsHigh correlation
occupation_ ? is highly correlated with workclass_ ?High correlation
relationship_ Husband is highly correlated with marital-status_ Married-civ-spouse and 3 other fieldsHigh correlation
relationship_ Not-in-family is highly correlated with marital-status_ Married-civ-spouseHigh correlation
relationship_ Own-child is highly correlated with marital-status_ Never-marriedHigh correlation
race_ Black is highly correlated with race_ WhiteHigh correlation
race_ White is highly correlated with race_ BlackHigh correlation
sex_ Female is highly correlated with relationship_ Husband and 1 other fieldsHigh correlation
sex_ Male is highly correlated with relationship_ Husband and 1 other fieldsHigh correlation
workclass_ ? is highly correlated with occupation_ ?High correlation
marital-status_ Married-civ-spouse is highly correlated with marital-status_ Never-married and 2 other fieldsHigh correlation
marital-status_ Never-married is highly correlated with marital-status_ Married-civ-spouse and 2 other fieldsHigh correlation
occupation_ ? is highly correlated with workclass_ ?High correlation
relationship_ Husband is highly correlated with marital-status_ Married-civ-spouse and 3 other fieldsHigh correlation
relationship_ Not-in-family is highly correlated with marital-status_ Married-civ-spouseHigh correlation
relationship_ Own-child is highly correlated with marital-status_ Never-marriedHigh correlation
race_ Black is highly correlated with race_ WhiteHigh correlation
race_ White is highly correlated with race_ BlackHigh correlation
sex_ Female is highly correlated with relationship_ Husband and 1 other fieldsHigh correlation
sex_ Male is highly correlated with relationship_ Husband and 1 other fieldsHigh correlation
sex_ Male is highly correlated with sex_ Female and 1 other fieldsHigh correlation
marital-status_ Married-civ-spouse is highly correlated with relationship_ Not-in-family and 2 other fieldsHigh correlation
occupation_ ? is highly correlated with workclass_ ?High correlation
relationship_ Own-child is highly correlated with marital-status_ Never-marriedHigh correlation
race_ White is highly correlated with race_ BlackHigh correlation
sex_ Female is highly correlated with sex_ Male and 1 other fieldsHigh correlation
relationship_ Not-in-family is highly correlated with marital-status_ Married-civ-spouseHigh correlation
race_ Black is highly correlated with race_ WhiteHigh correlation
workclass_ ? is highly correlated with occupation_ ?High correlation
relationship_ Husband is highly correlated with sex_ Male and 3 other fieldsHigh correlation
marital-status_ Never-married is highly correlated with marital-status_ Married-civ-spouse and 2 other fieldsHigh correlation
age is highly correlated with marital-status_ Never-married and 1 other fieldsHigh correlation
education-num is highly correlated with education_ 10th and 16 other fieldsHigh correlation
salary is highly correlated with marital-status_ Married-civ-spouse and 1 other fieldsHigh correlation
workclass_ ? is highly correlated with workclass_ Private and 1 other fieldsHigh correlation
workclass_ Local-gov is highly correlated with workclass_ PrivateHigh correlation
workclass_ Private is highly correlated with workclass_ ? and 3 other fieldsHigh correlation
workclass_ Self-emp-not-inc is highly correlated with workclass_ PrivateHigh correlation
education_ 10th is highly correlated with education-numHigh correlation
education_ 11th is highly correlated with education-numHigh correlation
education_ 12th is highly correlated with education-numHigh correlation
education_ 1st-4th is highly correlated with education-numHigh correlation
education_ 5th-6th is highly correlated with education-numHigh correlation
education_ 7th-8th is highly correlated with education-numHigh correlation
education_ 9th is highly correlated with education-numHigh correlation
education_ Assoc-acdm is highly correlated with education-numHigh correlation
education_ Bachelors is highly correlated with education-numHigh correlation
education_ Doctorate is highly correlated with education-numHigh correlation
education_ HS-grad is highly correlated with education-num and 1 other fieldsHigh correlation
education_ Masters is highly correlated with education-numHigh correlation
education_ Preschool is highly correlated with education-numHigh correlation
education_ Prof-school is highly correlated with education-numHigh correlation
education_ Some-college is highly correlated with education-num and 1 other fieldsHigh correlation
marital-status_ Divorced is highly correlated with marital-status_ Married-civ-spouseHigh correlation
marital-status_ Married-civ-spouse is highly correlated with salary and 7 other fieldsHigh correlation
marital-status_ Never-married is highly correlated with age and 3 other fieldsHigh correlation
occupation_ ? is highly correlated with workclass_ ? and 1 other fieldsHigh correlation
occupation_ Prof-specialty is highly correlated with education-numHigh correlation
relationship_ Husband is highly correlated with salary and 6 other fieldsHigh correlation
relationship_ Not-in-family is highly correlated with marital-status_ Married-civ-spouse and 1 other fieldsHigh correlation
relationship_ Own-child is highly correlated with age and 3 other fieldsHigh correlation
race_ Asian-Pac-Islander is highly correlated with race_ White and 2 other fieldsHigh correlation
race_ Black is highly correlated with race_ WhiteHigh correlation
race_ White is highly correlated with race_ Asian-Pac-Islander and 1 other fieldsHigh correlation
sex_ Female is highly correlated with marital-status_ Married-civ-spouse and 2 other fieldsHigh correlation
sex_ Male is highly correlated with marital-status_ Married-civ-spouse and 2 other fieldsHigh correlation
country_ ? is highly correlated with country_ United-StatesHigh correlation
country_ Mexico is highly correlated with education-num and 1 other fieldsHigh correlation
country_ Philippines is highly correlated with race_ Asian-Pac-IslanderHigh correlation
country_ United-States is highly correlated with race_ Asian-Pac-Islander and 2 other fieldsHigh correlation
capital-gain has 29849 (91.7%) zeros Zeros
capital-loss has 31042 (95.3%) zeros Zeros

Reproduction

Analysis started2022-06-25 12:19:04.579277
Analysis finished2022-06-25 12:22:27.231864
Duration3 minutes and 22.65 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

age
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct73
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.58164676
Minimum17
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size254.5 KiB
2022-06-25T17:52:27.462463image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile19
Q128
median37
Q348
95-th percentile63
Maximum90
Range73
Interquartile range (IQR)20

Descriptive statistics

Standard deviation13.64043255
Coefficient of variation (CV)0.3535471837
Kurtosis-0.1661274596
Mean38.58164676
Median Absolute Deviation (MAD)10
Skewness0.5587433694
Sum1256257
Variance186.0614002
MonotonicityNot monotonic
2022-06-25T17:52:28.031891image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36898
 
2.8%
31888
 
2.7%
34886
 
2.7%
23877
 
2.7%
35876
 
2.7%
33875
 
2.7%
28867
 
2.7%
30861
 
2.6%
37858
 
2.6%
25841
 
2.6%
Other values (63)23834
73.2%
ValueCountFrequency (%)
17395
1.2%
18550
1.7%
19712
2.2%
20753
2.3%
21720
2.2%
22765
2.3%
23877
2.7%
24798
2.5%
25841
2.6%
26785
2.4%
ValueCountFrequency (%)
9043
0.1%
883
 
< 0.1%
871
 
< 0.1%
861
 
< 0.1%
853
 
< 0.1%
8410
 
< 0.1%
836
 
< 0.1%
8212
 
< 0.1%
8120
0.1%
8022
0.1%

fnlwgt
Real number (ℝ≥0)

Distinct21648
Distinct (%)66.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean189778.3665
Minimum12285
Maximum1484705
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size254.5 KiB
2022-06-25T17:52:28.599027image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum12285
5-th percentile39460
Q1117827
median178356
Q3237051
95-th percentile379682
Maximum1484705
Range1472420
Interquartile range (IQR)119224

Descriptive statistics

Standard deviation105549.9777
Coefficient of variation (CV)0.5561749721
Kurtosis6.218810978
Mean189778.3665
Median Absolute Deviation (MAD)59894
Skewness1.446980095
Sum6179373392
Variance1.114079779 × 1010
MonotonicityNot monotonic
2022-06-25T17:52:29.184030image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16419013
 
< 0.1%
20348813
 
< 0.1%
12301113
 
< 0.1%
14899512
 
< 0.1%
12112412
 
< 0.1%
11336412
 
< 0.1%
12667512
 
< 0.1%
11148311
 
< 0.1%
12027711
 
< 0.1%
12398311
 
< 0.1%
Other values (21638)32441
99.6%
ValueCountFrequency (%)
122851
 
< 0.1%
137691
 
< 0.1%
148781
 
< 0.1%
188271
 
< 0.1%
192141
 
< 0.1%
193025
< 0.1%
193952
 
< 0.1%
194101
 
< 0.1%
194911
 
< 0.1%
195201
 
< 0.1%
ValueCountFrequency (%)
14847051
< 0.1%
14554351
< 0.1%
13661201
< 0.1%
12683391
< 0.1%
12265831
< 0.1%
11846221
< 0.1%
11613631
< 0.1%
11256131
< 0.1%
10974531
< 0.1%
10855151
< 0.1%

education-num
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.08067934
Minimum1
Maximum16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size254.5 KiB
2022-06-25T17:52:29.855700image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q19
median10
Q312
95-th percentile14
Maximum16
Range15
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.572720332
Coefficient of variation (CV)0.2552129916
Kurtosis0.6234440748
Mean10.08067934
Median Absolute Deviation (MAD)1
Skewness-0.3116758679
Sum328237
Variance6.618889907
MonotonicityNot monotonic
2022-06-25T17:52:30.371963image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
910501
32.3%
107291
22.4%
135355
16.4%
141723
 
5.3%
111382
 
4.2%
71175
 
3.6%
121067
 
3.3%
6933
 
2.9%
4646
 
2.0%
15576
 
1.8%
Other values (6)1912
 
5.9%
ValueCountFrequency (%)
151
 
0.2%
2168
 
0.5%
3333
 
1.0%
4646
 
2.0%
5514
 
1.6%
6933
 
2.9%
71175
 
3.6%
8433
 
1.3%
910501
32.3%
107291
22.4%
ValueCountFrequency (%)
16413
 
1.3%
15576
 
1.8%
141723
 
5.3%
135355
16.4%
121067
 
3.3%
111382
 
4.2%
107291
22.4%
910501
32.3%
8433
 
1.3%
71175
 
3.6%

capital-gain
Real number (ℝ≥0)

ZEROS

Distinct119
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1077.648844
Minimum0
Maximum99999
Zeros29849
Zeros (%)91.7%
Negative0
Negative (%)0.0%
Memory size254.5 KiB
2022-06-25T17:52:30.902541image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5013
Maximum99999
Range99999
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7385.292085
Coefficient of variation (CV)6.853152702
Kurtosis154.7994379
Mean1077.648844
Median Absolute Deviation (MAD)0
Skewness11.95384769
Sum35089324
Variance54542539.18
MonotonicityNot monotonic
2022-06-25T17:52:31.419171image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
029849
91.7%
15024347
 
1.1%
7688284
 
0.9%
7298246
 
0.8%
99999159
 
0.5%
517897
 
0.3%
310397
 
0.3%
438670
 
0.2%
501369
 
0.2%
861455
 
0.2%
Other values (109)1288
 
4.0%
ValueCountFrequency (%)
029849
91.7%
1146
 
< 0.1%
4012
 
< 0.1%
59434
 
0.1%
9148
 
< 0.1%
9915
 
< 0.1%
105525
 
0.1%
10864
 
< 0.1%
11111
 
< 0.1%
11518
 
< 0.1%
ValueCountFrequency (%)
99999159
0.5%
413102
 
< 0.1%
340955
 
< 0.1%
2782834
 
0.1%
2523611
 
< 0.1%
251244
 
< 0.1%
220401
 
< 0.1%
2005137
 
0.1%
184812
 
< 0.1%
158316
 
< 0.1%

capital-loss
Real number (ℝ≥0)

ZEROS

Distinct92
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.30382973
Minimum0
Maximum4356
Zeros31042
Zeros (%)95.3%
Negative0
Negative (%)0.0%
Memory size254.5 KiB
2022-06-25T17:52:32.090191image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum4356
Range4356
Interquartile range (IQR)0

Descriptive statistics

Standard deviation402.9602186
Coefficient of variation (CV)4.615607584
Kurtosis20.37680171
Mean87.30382973
Median Absolute Deviation (MAD)0
Skewness4.594629122
Sum2842700
Variance162376.9378
MonotonicityNot monotonic
2022-06-25T17:52:32.663264image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
031042
95.3%
1902202
 
0.6%
1977168
 
0.5%
1887159
 
0.5%
184851
 
0.2%
148551
 
0.2%
241549
 
0.2%
160247
 
0.1%
174042
 
0.1%
159040
 
0.1%
Other values (82)710
 
2.2%
ValueCountFrequency (%)
031042
95.3%
1551
 
< 0.1%
2134
 
< 0.1%
3233
 
< 0.1%
4193
 
< 0.1%
62512
 
< 0.1%
6533
 
< 0.1%
8102
 
< 0.1%
8806
 
< 0.1%
9742
 
< 0.1%
ValueCountFrequency (%)
43563
 
< 0.1%
39002
 
< 0.1%
37702
 
< 0.1%
36832
 
< 0.1%
30042
 
< 0.1%
282410
< 0.1%
27542
 
< 0.1%
26035
< 0.1%
255912
< 0.1%
25474
 
< 0.1%

hours-per-week
Real number (ℝ≥0)

Distinct94
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.43745585
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size254.5 KiB
2022-06-25T17:52:33.367139image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18
Q140
median40
Q345
95-th percentile60
Maximum99
Range98
Interquartile range (IQR)5

Descriptive statistics

Standard deviation12.34742868
Coefficient of variation (CV)0.3053463286
Kurtosis2.916686796
Mean40.43745585
Median Absolute Deviation (MAD)3
Skewness0.2276425368
Sum1316684
Variance152.4589951
MonotonicityNot monotonic
2022-06-25T17:52:33.981542image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4015217
46.7%
502819
 
8.7%
451824
 
5.6%
601475
 
4.5%
351297
 
4.0%
201224
 
3.8%
301149
 
3.5%
55694
 
2.1%
25674
 
2.1%
48517
 
1.6%
Other values (84)5671
 
17.4%
ValueCountFrequency (%)
120
 
0.1%
232
 
0.1%
339
 
0.1%
454
 
0.2%
560
 
0.2%
664
 
0.2%
726
 
0.1%
8145
0.4%
918
 
0.1%
10278
0.9%
ValueCountFrequency (%)
9985
0.3%
9811
 
< 0.1%
972
 
< 0.1%
965
 
< 0.1%
952
 
< 0.1%
941
 
< 0.1%
921
 
< 0.1%
913
 
< 0.1%
9029
 
0.1%
892
 
< 0.1%

salary
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
24720 
1
7841 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
024720
75.9%
17841
 
24.1%

Length

2022-06-25T17:52:34.521884image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:35.092918image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
024720
75.9%
17841
 
24.1%

Most occurring characters

ValueCountFrequency (%)
024720
75.9%
17841
 
24.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
024720
75.9%
17841
 
24.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
024720
75.9%
17841
 
24.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
024720
75.9%
17841
 
24.1%

workclass_ ?
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
30725 
1
 
1836

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
030725
94.4%
11836
 
5.6%

Length

2022-06-25T17:52:35.605130image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:36.145245image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
030725
94.4%
11836
 
5.6%

Most occurring characters

ValueCountFrequency (%)
030725
94.4%
11836
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
030725
94.4%
11836
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
030725
94.4%
11836
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
030725
94.4%
11836
 
5.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31601 
1
 
960

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031601
97.1%
1960
 
2.9%

Length

2022-06-25T17:52:36.620623image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:37.181053image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031601
97.1%
1960
 
2.9%

Most occurring characters

ValueCountFrequency (%)
031601
97.1%
1960
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031601
97.1%
1960
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031601
97.1%
1960
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031601
97.1%
1960
 
2.9%

workclass_ Local-gov
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
30468 
1
 
2093

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
030468
93.6%
12093
 
6.4%

Length

2022-06-25T17:52:37.658814image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:38.161393image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
030468
93.6%
12093
 
6.4%

Most occurring characters

ValueCountFrequency (%)
030468
93.6%
12093
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
030468
93.6%
12093
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
030468
93.6%
12093
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
030468
93.6%
12093
 
6.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32554 
1
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032554
> 99.9%
17
 
< 0.1%

Length

2022-06-25T17:52:38.626383image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:39.143768image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032554
> 99.9%
17
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
032554
> 99.9%
17
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032554
> 99.9%
17
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032554
> 99.9%
17
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032554
> 99.9%
17
 
< 0.1%

workclass_ Private
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
1
22696 
0
9865 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
122696
69.7%
09865
30.3%

Length

2022-06-25T17:52:39.840451image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:40.410819image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
122696
69.7%
09865
30.3%

Most occurring characters

ValueCountFrequency (%)
122696
69.7%
09865
30.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
122696
69.7%
09865
30.3%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
122696
69.7%
09865
30.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
122696
69.7%
09865
30.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31445 
1
 
1116

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031445
96.6%
11116
 
3.4%

Length

2022-06-25T17:52:40.947538image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:41.431612image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031445
96.6%
11116
 
3.4%

Most occurring characters

ValueCountFrequency (%)
031445
96.6%
11116
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031445
96.6%
11116
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031445
96.6%
11116
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031445
96.6%
11116
 
3.4%

workclass_ Self-emp-not-inc
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
30020 
1
 
2541

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
030020
92.2%
12541
 
7.8%

Length

2022-06-25T17:52:41.870336image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:42.262622image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
030020
92.2%
12541
 
7.8%

Most occurring characters

ValueCountFrequency (%)
030020
92.2%
12541
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
030020
92.2%
12541
 
7.8%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
030020
92.2%
12541
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
030020
92.2%
12541
 
7.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31263 
1
 
1298

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031263
96.0%
11298
 
4.0%

Length

2022-06-25T17:52:42.643523image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:43.077305image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031263
96.0%
11298
 
4.0%

Most occurring characters

ValueCountFrequency (%)
031263
96.0%
11298
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031263
96.0%
11298
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031263
96.0%
11298
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031263
96.0%
11298
 
4.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32547 
1
 
14

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032547
> 99.9%
114
 
< 0.1%

Length

2022-06-25T17:52:43.315313image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:43.543098image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032547
> 99.9%
114
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
032547
> 99.9%
114
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032547
> 99.9%
114
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032547
> 99.9%
114
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032547
> 99.9%
114
 
< 0.1%

education_ 10th
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31628 
1
 
933

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031628
97.1%
1933
 
2.9%

Length

2022-06-25T17:52:43.821519image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:44.078956image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031628
97.1%
1933
 
2.9%

Most occurring characters

ValueCountFrequency (%)
031628
97.1%
1933
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031628
97.1%
1933
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031628
97.1%
1933
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031628
97.1%
1933
 
2.9%

education_ 11th
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31386 
1
 
1175

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
031386
96.4%
11175
 
3.6%

Length

2022-06-25T17:52:44.416620image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:44.822870image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031386
96.4%
11175
 
3.6%

Most occurring characters

ValueCountFrequency (%)
031386
96.4%
11175
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031386
96.4%
11175
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031386
96.4%
11175
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031386
96.4%
11175
 
3.6%

education_ 12th
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32128 
1
 
433

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032128
98.7%
1433
 
1.3%

Length

2022-06-25T17:52:45.338272image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:45.825538image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032128
98.7%
1433
 
1.3%

Most occurring characters

ValueCountFrequency (%)
032128
98.7%
1433
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032128
98.7%
1433
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032128
98.7%
1433
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032128
98.7%
1433
 
1.3%

education_ 1st-4th
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32393 
1
 
168

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032393
99.5%
1168
 
0.5%

Length

2022-06-25T17:52:46.373568image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:46.902795image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032393
99.5%
1168
 
0.5%

Most occurring characters

ValueCountFrequency (%)
032393
99.5%
1168
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032393
99.5%
1168
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032393
99.5%
1168
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032393
99.5%
1168
 
0.5%

education_ 5th-6th
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32228 
1
 
333

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032228
99.0%
1333
 
1.0%

Length

2022-06-25T17:52:47.401846image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:47.885692image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032228
99.0%
1333
 
1.0%

Most occurring characters

ValueCountFrequency (%)
032228
99.0%
1333
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032228
99.0%
1333
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032228
99.0%
1333
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032228
99.0%
1333
 
1.0%

education_ 7th-8th
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31915 
1
 
646

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031915
98.0%
1646
 
2.0%

Length

2022-06-25T17:52:48.409733image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:48.892454image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031915
98.0%
1646
 
2.0%

Most occurring characters

ValueCountFrequency (%)
031915
98.0%
1646
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031915
98.0%
1646
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031915
98.0%
1646
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031915
98.0%
1646
 
2.0%

education_ 9th
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32047 
1
 
514

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032047
98.4%
1514
 
1.6%

Length

2022-06-25T17:52:49.385094image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:49.939384image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032047
98.4%
1514
 
1.6%

Most occurring characters

ValueCountFrequency (%)
032047
98.4%
1514
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032047
98.4%
1514
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032047
98.4%
1514
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032047
98.4%
1514
 
1.6%

education_ Assoc-acdm
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31494 
1
 
1067

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031494
96.7%
11067
 
3.3%

Length

2022-06-25T17:52:50.410576image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:50.934523image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031494
96.7%
11067
 
3.3%

Most occurring characters

ValueCountFrequency (%)
031494
96.7%
11067
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031494
96.7%
11067
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031494
96.7%
11067
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031494
96.7%
11067
 
3.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31179 
1
 
1382

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031179
95.8%
11382
 
4.2%

Length

2022-06-25T17:52:51.422609image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:51.924369image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031179
95.8%
11382
 
4.2%

Most occurring characters

ValueCountFrequency (%)
031179
95.8%
11382
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031179
95.8%
11382
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031179
95.8%
11382
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031179
95.8%
11382
 
4.2%

education_ Bachelors
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
27206 
1
5355 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
027206
83.6%
15355
 
16.4%

Length

2022-06-25T17:52:52.471715image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:53.273300image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
027206
83.6%
15355
 
16.4%

Most occurring characters

ValueCountFrequency (%)
027206
83.6%
15355
 
16.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
027206
83.6%
15355
 
16.4%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
027206
83.6%
15355
 
16.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
027206
83.6%
15355
 
16.4%

education_ Doctorate
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32148 
1
 
413

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032148
98.7%
1413
 
1.3%

Length

2022-06-25T17:52:53.789138image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:54.286628image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032148
98.7%
1413
 
1.3%

Most occurring characters

ValueCountFrequency (%)
032148
98.7%
1413
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032148
98.7%
1413
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032148
98.7%
1413
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032148
98.7%
1413
 
1.3%

education_ HS-grad
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
22060 
1
10501 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
022060
67.7%
110501
32.3%

Length

2022-06-25T17:52:54.783611image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:55.311436image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
022060
67.7%
110501
32.3%

Most occurring characters

ValueCountFrequency (%)
022060
67.7%
110501
32.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
022060
67.7%
110501
32.3%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
022060
67.7%
110501
32.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
022060
67.7%
110501
32.3%

education_ Masters
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
30838 
1
 
1723

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
030838
94.7%
11723
 
5.3%

Length

2022-06-25T17:52:55.708114image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:56.269047image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
030838
94.7%
11723
 
5.3%

Most occurring characters

ValueCountFrequency (%)
030838
94.7%
11723
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
030838
94.7%
11723
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
030838
94.7%
11723
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
030838
94.7%
11723
 
5.3%

education_ Preschool
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32510 
1
 
51

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032510
99.8%
151
 
0.2%

Length

2022-06-25T17:52:56.734688image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:57.214580image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032510
99.8%
151
 
0.2%

Most occurring characters

ValueCountFrequency (%)
032510
99.8%
151
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032510
99.8%
151
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032510
99.8%
151
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032510
99.8%
151
 
0.2%

education_ Prof-school
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31985 
1
 
576

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031985
98.2%
1576
 
1.8%

Length

2022-06-25T17:52:57.711023image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:58.135215image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031985
98.2%
1576
 
1.8%

Most occurring characters

ValueCountFrequency (%)
031985
98.2%
1576
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031985
98.2%
1576
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031985
98.2%
1576
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031985
98.2%
1576
 
1.8%

education_ Some-college
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
25270 
1
7291 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
025270
77.6%
17291
 
22.4%

Length

2022-06-25T17:52:58.432226image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:58.908071image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
025270
77.6%
17291
 
22.4%

Most occurring characters

ValueCountFrequency (%)
025270
77.6%
17291
 
22.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
025270
77.6%
17291
 
22.4%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
025270
77.6%
17291
 
22.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
025270
77.6%
17291
 
22.4%

marital-status_ Divorced
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
28118 
1
4443 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
028118
86.4%
14443
 
13.6%

Length

2022-06-25T17:52:59.130557image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:52:59.364132image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
028118
86.4%
14443
 
13.6%

Most occurring characters

ValueCountFrequency (%)
028118
86.4%
14443
 
13.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
028118
86.4%
14443
 
13.6%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
028118
86.4%
14443
 
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
028118
86.4%
14443
 
13.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32538 
1
 
23

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032538
99.9%
123
 
0.1%

Length

2022-06-25T17:52:59.685040image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:00.040088image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032538
99.9%
123
 
0.1%

Most occurring characters

ValueCountFrequency (%)
032538
99.9%
123
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032538
99.9%
123
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032538
99.9%
123
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032538
99.9%
123
 
0.1%

marital-status_ Married-civ-spouse
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
17585 
1
14976 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
017585
54.0%
114976
46.0%

Length

2022-06-25T17:53:00.489715image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:00.996171image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
017585
54.0%
114976
46.0%

Most occurring characters

ValueCountFrequency (%)
017585
54.0%
114976
46.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
017585
54.0%
114976
46.0%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
017585
54.0%
114976
46.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
017585
54.0%
114976
46.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32143 
1
 
418

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032143
98.7%
1418
 
1.3%

Length

2022-06-25T17:53:01.471321image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:02.015905image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032143
98.7%
1418
 
1.3%

Most occurring characters

ValueCountFrequency (%)
032143
98.7%
1418
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032143
98.7%
1418
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032143
98.7%
1418
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032143
98.7%
1418
 
1.3%

marital-status_ Never-married
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
21878 
1
10683 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
021878
67.2%
110683
32.8%

Length

2022-06-25T17:53:02.490759image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:02.967547image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
021878
67.2%
110683
32.8%

Most occurring characters

ValueCountFrequency (%)
021878
67.2%
110683
32.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
021878
67.2%
110683
32.8%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
021878
67.2%
110683
32.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
021878
67.2%
110683
32.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31536 
1
 
1025

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031536
96.9%
11025
 
3.1%

Length

2022-06-25T17:53:03.455060image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:03.961478image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031536
96.9%
11025
 
3.1%

Most occurring characters

ValueCountFrequency (%)
031536
96.9%
11025
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031536
96.9%
11025
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031536
96.9%
11025
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031536
96.9%
11025
 
3.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31568 
1
 
993

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031568
97.0%
1993
 
3.0%

Length

2022-06-25T17:53:04.409425image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:04.924143image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031568
97.0%
1993
 
3.0%

Most occurring characters

ValueCountFrequency (%)
031568
97.0%
1993
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031568
97.0%
1993
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031568
97.0%
1993
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031568
97.0%
1993
 
3.0%

occupation_ ?
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
30718 
1
 
1843

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
030718
94.3%
11843
 
5.7%

Length

2022-06-25T17:53:05.376781image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:05.905534image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
030718
94.3%
11843
 
5.7%

Most occurring characters

ValueCountFrequency (%)
030718
94.3%
11843
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
030718
94.3%
11843
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
030718
94.3%
11843
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
030718
94.3%
11843
 
5.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
28791 
1
3770 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
028791
88.4%
13770
 
11.6%

Length

2022-06-25T17:53:06.585412image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:07.113302image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
028791
88.4%
13770
 
11.6%

Most occurring characters

ValueCountFrequency (%)
028791
88.4%
13770
 
11.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
028791
88.4%
13770
 
11.6%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
028791
88.4%
13770
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
028791
88.4%
13770
 
11.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32552 
1
 
9

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032552
> 99.9%
19
 
< 0.1%

Length

2022-06-25T17:53:07.574601image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:08.124246image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032552
> 99.9%
19
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
032552
> 99.9%
19
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032552
> 99.9%
19
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032552
> 99.9%
19
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032552
> 99.9%
19
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
28462 
1
4099 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
028462
87.4%
14099
 
12.6%

Length

2022-06-25T17:53:08.615947image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:09.203228image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
028462
87.4%
14099
 
12.6%

Most occurring characters

ValueCountFrequency (%)
028462
87.4%
14099
 
12.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
028462
87.4%
14099
 
12.6%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
028462
87.4%
14099
 
12.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
028462
87.4%
14099
 
12.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
28495 
1
4066 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
028495
87.5%
14066
 
12.5%

Length

2022-06-25T17:53:09.687846image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:10.180299image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
028495
87.5%
14066
 
12.5%

Most occurring characters

ValueCountFrequency (%)
028495
87.5%
14066
 
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
028495
87.5%
14066
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
028495
87.5%
14066
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
028495
87.5%
14066
 
12.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31567 
1
 
994

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031567
96.9%
1994
 
3.1%

Length

2022-06-25T17:53:10.643623image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:11.165396image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031567
96.9%
1994
 
3.1%

Most occurring characters

ValueCountFrequency (%)
031567
96.9%
1994
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031567
96.9%
1994
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031567
96.9%
1994
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031567
96.9%
1994
 
3.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31191 
1
 
1370

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
031191
95.8%
11370
 
4.2%

Length

2022-06-25T17:53:11.701653image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:12.252063image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031191
95.8%
11370
 
4.2%

Most occurring characters

ValueCountFrequency (%)
031191
95.8%
11370
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031191
95.8%
11370
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031191
95.8%
11370
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031191
95.8%
11370
 
4.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
30559 
1
 
2002

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
030559
93.9%
12002
 
6.1%

Length

2022-06-25T17:53:12.723901image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:13.260115image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
030559
93.9%
12002
 
6.1%

Most occurring characters

ValueCountFrequency (%)
030559
93.9%
12002
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
030559
93.9%
12002
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
030559
93.9%
12002
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
030559
93.9%
12002
 
6.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
29266 
1
3295 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
029266
89.9%
13295
 
10.1%

Length

2022-06-25T17:53:13.681876image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:14.090786image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
029266
89.9%
13295
 
10.1%

Most occurring characters

ValueCountFrequency (%)
029266
89.9%
13295
 
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
029266
89.9%
13295
 
10.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
029266
89.9%
13295
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
029266
89.9%
13295
 
10.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32412 
1
 
149

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032412
99.5%
1149
 
0.5%

Length

2022-06-25T17:53:14.510210image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:14.993016image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032412
99.5%
1149
 
0.5%

Most occurring characters

ValueCountFrequency (%)
032412
99.5%
1149
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032412
99.5%
1149
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032412
99.5%
1149
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032412
99.5%
1149
 
0.5%

occupation_ Prof-specialty
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
28421 
1
4140 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
028421
87.3%
14140
 
12.7%

Length

2022-06-25T17:53:15.250933image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:15.493819image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
028421
87.3%
14140
 
12.7%

Most occurring characters

ValueCountFrequency (%)
028421
87.3%
14140
 
12.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
028421
87.3%
14140
 
12.7%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
028421
87.3%
14140
 
12.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
028421
87.3%
14140
 
12.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31912 
1
 
649

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031912
98.0%
1649
 
2.0%

Length

2022-06-25T17:53:15.776412image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:16.151871image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031912
98.0%
1649
 
2.0%

Most occurring characters

ValueCountFrequency (%)
031912
98.0%
1649
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031912
98.0%
1649
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031912
98.0%
1649
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031912
98.0%
1649
 
2.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
28911 
1
3650 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
028911
88.8%
13650
 
11.2%

Length

2022-06-25T17:53:16.542491image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:17.066980image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
028911
88.8%
13650
 
11.2%

Most occurring characters

ValueCountFrequency (%)
028911
88.8%
13650
 
11.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
028911
88.8%
13650
 
11.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
028911
88.8%
13650
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
028911
88.8%
13650
 
11.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31633 
1
 
928

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031633
97.1%
1928
 
2.9%

Length

2022-06-25T17:53:17.562314image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:18.084190image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031633
97.1%
1928
 
2.9%

Most occurring characters

ValueCountFrequency (%)
031633
97.1%
1928
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031633
97.1%
1928
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031633
97.1%
1928
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031633
97.1%
1928
 
2.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
30964 
1
 
1597

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
030964
95.1%
11597
 
4.9%

Length

2022-06-25T17:53:18.585099image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:19.087920image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
030964
95.1%
11597
 
4.9%

Most occurring characters

ValueCountFrequency (%)
030964
95.1%
11597
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
030964
95.1%
11597
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
030964
95.1%
11597
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
030964
95.1%
11597
 
4.9%

relationship_ Husband
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
19368 
1
13193 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
019368
59.5%
113193
40.5%

Length

2022-06-25T17:53:19.586788image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:20.126324image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
019368
59.5%
113193
40.5%

Most occurring characters

ValueCountFrequency (%)
019368
59.5%
113193
40.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
019368
59.5%
113193
40.5%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
019368
59.5%
113193
40.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
019368
59.5%
113193
40.5%

relationship_ Not-in-family
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
24256 
1
8305 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
024256
74.5%
18305
 
25.5%

Length

2022-06-25T17:53:20.906754image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:21.399056image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
024256
74.5%
18305
 
25.5%

Most occurring characters

ValueCountFrequency (%)
024256
74.5%
18305
 
25.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
024256
74.5%
18305
 
25.5%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
024256
74.5%
18305
 
25.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
024256
74.5%
18305
 
25.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31580 
1
 
981

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031580
97.0%
1981
 
3.0%

Length

2022-06-25T17:53:21.886417image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:22.365143image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031580
97.0%
1981
 
3.0%

Most occurring characters

ValueCountFrequency (%)
031580
97.0%
1981
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031580
97.0%
1981
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031580
97.0%
1981
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031580
97.0%
1981
 
3.0%

relationship_ Own-child
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
27493 
1
5068 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
027493
84.4%
15068
 
15.6%

Length

2022-06-25T17:53:22.915921image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:23.393984image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
027493
84.4%
15068
 
15.6%

Most occurring characters

ValueCountFrequency (%)
027493
84.4%
15068
 
15.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
027493
84.4%
15068
 
15.6%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
027493
84.4%
15068
 
15.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
027493
84.4%
15068
 
15.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
29115 
1
3446 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
029115
89.4%
13446
 
10.6%

Length

2022-06-25T17:53:23.875294image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:24.475403image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
029115
89.4%
13446
 
10.6%

Most occurring characters

ValueCountFrequency (%)
029115
89.4%
13446
 
10.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
029115
89.4%
13446
 
10.6%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
029115
89.4%
13446
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
029115
89.4%
13446
 
10.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
30993 
1
 
1568

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
030993
95.2%
11568
 
4.8%

Length

2022-06-25T17:53:25.131204image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:25.641842image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
030993
95.2%
11568
 
4.8%

Most occurring characters

ValueCountFrequency (%)
030993
95.2%
11568
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
030993
95.2%
11568
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
030993
95.2%
11568
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
030993
95.2%
11568
 
4.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32250 
1
 
311

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032250
99.0%
1311
 
1.0%

Length

2022-06-25T17:53:26.019427image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:26.294701image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032250
99.0%
1311
 
1.0%

Most occurring characters

ValueCountFrequency (%)
032250
99.0%
1311
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032250
99.0%
1311
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032250
99.0%
1311
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032250
99.0%
1311
 
1.0%

race_ Asian-Pac-Islander
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31522 
1
 
1039

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031522
96.8%
11039
 
3.2%

Length

2022-06-25T17:53:26.755190image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:27.286654image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031522
96.8%
11039
 
3.2%

Most occurring characters

ValueCountFrequency (%)
031522
96.8%
11039
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031522
96.8%
11039
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031522
96.8%
11039
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031522
96.8%
11039
 
3.2%

race_ Black
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
29437 
1
3124 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
029437
90.4%
13124
 
9.6%

Length

2022-06-25T17:53:27.895260image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:28.397609image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
029437
90.4%
13124
 
9.6%

Most occurring characters

ValueCountFrequency (%)
029437
90.4%
13124
 
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
029437
90.4%
13124
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
029437
90.4%
13124
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
029437
90.4%
13124
 
9.6%

race_ Other
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32290 
1
 
271

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032290
99.2%
1271
 
0.8%

Length

2022-06-25T17:53:28.869316image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:29.371209image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032290
99.2%
1271
 
0.8%

Most occurring characters

ValueCountFrequency (%)
032290
99.2%
1271
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032290
99.2%
1271
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032290
99.2%
1271
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032290
99.2%
1271
 
0.8%

race_ White
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
1
27816 
0
4745 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
127816
85.4%
04745
 
14.6%

Length

2022-06-25T17:53:30.056615image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:30.755185image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
127816
85.4%
04745
 
14.6%

Most occurring characters

ValueCountFrequency (%)
127816
85.4%
04745
 
14.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
127816
85.4%
04745
 
14.6%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
127816
85.4%
04745
 
14.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127816
85.4%
04745
 
14.6%

sex_ Female
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
21790 
1
10771 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
021790
66.9%
110771
33.1%

Length

2022-06-25T17:53:31.122817image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:31.431284image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
021790
66.9%
110771
33.1%

Most occurring characters

ValueCountFrequency (%)
021790
66.9%
110771
33.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
021790
66.9%
110771
33.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
021790
66.9%
110771
33.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
021790
66.9%
110771
33.1%

sex_ Male
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
1
21790 
0
10771 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
121790
66.9%
010771
33.1%

Length

2022-06-25T17:53:31.676226image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:31.947336image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
121790
66.9%
010771
33.1%

Most occurring characters

ValueCountFrequency (%)
121790
66.9%
010771
33.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
121790
66.9%
010771
33.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
121790
66.9%
010771
33.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
121790
66.9%
010771
33.1%

country_ ?
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31978 
1
 
583

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031978
98.2%
1583
 
1.8%

Length

2022-06-25T17:53:32.245699image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:32.654399image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031978
98.2%
1583
 
1.8%

Most occurring characters

ValueCountFrequency (%)
031978
98.2%
1583
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031978
98.2%
1583
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031978
98.2%
1583
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031978
98.2%
1583
 
1.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32542 
1
 
19

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032542
99.9%
119
 
0.1%

Length

2022-06-25T17:53:33.329062image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:34.167128image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032542
99.9%
119
 
0.1%

Most occurring characters

ValueCountFrequency (%)
032542
99.9%
119
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032542
99.9%
119
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032542
99.9%
119
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032542
99.9%
119
 
0.1%

country_ Canada
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32440 
1
 
121

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032440
99.6%
1121
 
0.4%

Length

2022-06-25T17:53:34.952507image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:35.551782image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032440
99.6%
1121
 
0.4%

Most occurring characters

ValueCountFrequency (%)
032440
99.6%
1121
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032440
99.6%
1121
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032440
99.6%
1121
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032440
99.6%
1121
 
0.4%

country_ China
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32486 
1
 
75

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032486
99.8%
175
 
0.2%

Length

2022-06-25T17:53:36.423443image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:37.109512image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032486
99.8%
175
 
0.2%

Most occurring characters

ValueCountFrequency (%)
032486
99.8%
175
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032486
99.8%
175
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032486
99.8%
175
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032486
99.8%
175
 
0.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32502 
1
 
59

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032502
99.8%
159
 
0.2%

Length

2022-06-25T17:53:37.795313image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:38.419505image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032502
99.8%
159
 
0.2%

Most occurring characters

ValueCountFrequency (%)
032502
99.8%
159
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032502
99.8%
159
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032502
99.8%
159
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032502
99.8%
159
 
0.2%

country_ Cuba
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32466 
1
 
95

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
032466
99.7%
195
 
0.3%

Length

2022-06-25T17:53:38.916201image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:39.470714image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032466
99.7%
195
 
0.3%

Most occurring characters

ValueCountFrequency (%)
032466
99.7%
195
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032466
99.7%
195
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032466
99.7%
195
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032466
99.7%
195
 
0.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32491 
1
 
70

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032491
99.8%
170
 
0.2%

Length

2022-06-25T17:53:39.952264image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:40.490105image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032491
99.8%
170
 
0.2%

Most occurring characters

ValueCountFrequency (%)
032491
99.8%
170
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032491
99.8%
170
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032491
99.8%
170
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032491
99.8%
170
 
0.2%

country_ Ecuador
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32533 
1
 
28

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032533
99.9%
128
 
0.1%

Length

2022-06-25T17:53:40.966381image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:41.586457image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032533
99.9%
128
 
0.1%

Most occurring characters

ValueCountFrequency (%)
032533
99.9%
128
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032533
99.9%
128
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032533
99.9%
128
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032533
99.9%
128
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32455 
1
 
106

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032455
99.7%
1106
 
0.3%

Length

2022-06-25T17:53:42.041582image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:42.594454image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032455
99.7%
1106
 
0.3%

Most occurring characters

ValueCountFrequency (%)
032455
99.7%
1106
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032455
99.7%
1106
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032455
99.7%
1106
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032455
99.7%
1106
 
0.3%

country_ England
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32471 
1
 
90

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032471
99.7%
190
 
0.3%

Length

2022-06-25T17:53:43.117057image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:43.641000image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032471
99.7%
190
 
0.3%

Most occurring characters

ValueCountFrequency (%)
032471
99.7%
190
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032471
99.7%
190
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032471
99.7%
190
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032471
99.7%
190
 
0.3%

country_ France
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32532 
1
 
29

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032532
99.9%
129
 
0.1%

Length

2022-06-25T17:53:44.189295image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:44.771686image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032532
99.9%
129
 
0.1%

Most occurring characters

ValueCountFrequency (%)
032532
99.9%
129
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032532
99.9%
129
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032532
99.9%
129
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032532
99.9%
129
 
0.1%

country_ Germany
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32424 
1
 
137

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032424
99.6%
1137
 
0.4%

Length

2022-06-25T17:53:45.213511image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:45.661364image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032424
99.6%
1137
 
0.4%

Most occurring characters

ValueCountFrequency (%)
032424
99.6%
1137
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032424
99.6%
1137
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032424
99.6%
1137
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032424
99.6%
1137
 
0.4%

country_ Greece
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32532 
1
 
29

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032532
99.9%
129
 
0.1%

Length

2022-06-25T17:53:46.069490image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:46.479355image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032532
99.9%
129
 
0.1%

Most occurring characters

ValueCountFrequency (%)
032532
99.9%
129
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032532
99.9%
129
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032532
99.9%
129
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032532
99.9%
129
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32497 
1
 
64

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032497
99.8%
164
 
0.2%

Length

2022-06-25T17:53:46.927826image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:47.211058image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032497
99.8%
164
 
0.2%

Most occurring characters

ValueCountFrequency (%)
032497
99.8%
164
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032497
99.8%
164
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032497
99.8%
164
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032497
99.8%
164
 
0.2%

country_ Haiti
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32517 
1
 
44

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032517
99.9%
144
 
0.1%

Length

2022-06-25T17:53:47.438092image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:47.712326image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032517
99.9%
144
 
0.1%

Most occurring characters

ValueCountFrequency (%)
032517
99.9%
144
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032517
99.9%
144
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032517
99.9%
144
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032517
99.9%
144
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32560 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032560
> 99.9%
11
 
< 0.1%

Length

2022-06-25T17:53:48.040198image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:48.489269image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032560
> 99.9%
11
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
032560
> 99.9%
11
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032560
> 99.9%
11
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032560
> 99.9%
11
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032560
> 99.9%
11
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32548 
1
 
13

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032548
> 99.9%
113
 
< 0.1%

Length

2022-06-25T17:53:48.963300image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:49.527283image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032548
> 99.9%
113
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
032548
> 99.9%
113
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032548
> 99.9%
113
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032548
> 99.9%
113
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032548
> 99.9%
113
 
< 0.1%

country_ Hong
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32541 
1
 
20

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032541
99.9%
120
 
0.1%

Length

2022-06-25T17:53:49.790820image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:50.303226image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032541
99.9%
120
 
0.1%

Most occurring characters

ValueCountFrequency (%)
032541
99.9%
120
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032541
99.9%
120
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032541
99.9%
120
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032541
99.9%
120
 
0.1%

country_ Hungary
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32548 
1
 
13

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032548
> 99.9%
113
 
< 0.1%

Length

2022-06-25T17:53:51.043857image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:51.499292image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032548
> 99.9%
113
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
032548
> 99.9%
113
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032548
> 99.9%
113
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032548
> 99.9%
113
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032548
> 99.9%
113
 
< 0.1%

country_ India
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32461 
1
 
100

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032461
99.7%
1100
 
0.3%

Length

2022-06-25T17:53:51.964747image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:52.489766image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032461
99.7%
1100
 
0.3%

Most occurring characters

ValueCountFrequency (%)
032461
99.7%
1100
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032461
99.7%
1100
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032461
99.7%
1100
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032461
99.7%
1100
 
0.3%

country_ Iran
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32518 
1
 
43

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032518
99.9%
143
 
0.1%

Length

2022-06-25T17:53:52.967801image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:53.564606image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032518
99.9%
143
 
0.1%

Most occurring characters

ValueCountFrequency (%)
032518
99.9%
143
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032518
99.9%
143
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032518
99.9%
143
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032518
99.9%
143
 
0.1%

country_ Ireland
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32537 
1
 
24

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032537
99.9%
124
 
0.1%

Length

2022-06-25T17:53:54.036179image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:54.550834image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032537
99.9%
124
 
0.1%

Most occurring characters

ValueCountFrequency (%)
032537
99.9%
124
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032537
99.9%
124
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032537
99.9%
124
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032537
99.9%
124
 
0.1%

country_ Italy
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32488 
1
 
73

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032488
99.8%
173
 
0.2%

Length

2022-06-25T17:53:55.067010image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:55.658289image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032488
99.8%
173
 
0.2%

Most occurring characters

ValueCountFrequency (%)
032488
99.8%
173
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032488
99.8%
173
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032488
99.8%
173
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032488
99.8%
173
 
0.2%

country_ Jamaica
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32480 
1
 
81

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032480
99.8%
181
 
0.2%

Length

2022-06-25T17:53:56.151420image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:56.668738image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032480
99.8%
181
 
0.2%

Most occurring characters

ValueCountFrequency (%)
032480
99.8%
181
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032480
99.8%
181
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032480
99.8%
181
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032480
99.8%
181
 
0.2%

country_ Japan
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32499 
1
 
62

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032499
99.8%
162
 
0.2%

Length

2022-06-25T17:53:57.100397image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:57.600687image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032499
99.8%
162
 
0.2%

Most occurring characters

ValueCountFrequency (%)
032499
99.8%
162
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032499
99.8%
162
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032499
99.8%
162
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032499
99.8%
162
 
0.2%

country_ Laos
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32543 
1
 
18

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032543
99.9%
118
 
0.1%

Length

2022-06-25T17:53:58.096842image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:58.657983image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032543
99.9%
118
 
0.1%

Most occurring characters

ValueCountFrequency (%)
032543
99.9%
118
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032543
99.9%
118
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032543
99.9%
118
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032543
99.9%
118
 
0.1%

country_ Mexico
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
31918 
1
 
643

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
031918
98.0%
1643
 
2.0%

Length

2022-06-25T17:53:59.169118image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:53:59.677485image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
031918
98.0%
1643
 
2.0%

Most occurring characters

ValueCountFrequency (%)
031918
98.0%
1643
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031918
98.0%
1643
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031918
98.0%
1643
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031918
98.0%
1643
 
2.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32527 
1
 
34

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032527
99.9%
134
 
0.1%

Length

2022-06-25T17:54:00.207499image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:54:00.658527image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032527
99.9%
134
 
0.1%

Most occurring characters

ValueCountFrequency (%)
032527
99.9%
134
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032527
99.9%
134
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032527
99.9%
134
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032527
99.9%
134
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32547 
1
 
14

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032547
> 99.9%
114
 
< 0.1%

Length

2022-06-25T17:54:01.148153image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:54:01.627344image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032547
> 99.9%
114
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
032547
> 99.9%
114
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032547
> 99.9%
114
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032547
> 99.9%
114
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032547
> 99.9%
114
 
< 0.1%

country_ Peru
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32530 
1
 
31

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032530
99.9%
131
 
0.1%

Length

2022-06-25T17:54:02.081903image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:54:02.393176image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032530
99.9%
131
 
0.1%

Most occurring characters

ValueCountFrequency (%)
032530
99.9%
131
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032530
99.9%
131
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032530
99.9%
131
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032530
99.9%
131
 
0.1%

country_ Philippines
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32363 
1
 
198

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032363
99.4%
1198
 
0.6%

Length

2022-06-25T17:54:02.829632image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:54:03.171118image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032363
99.4%
1198
 
0.6%

Most occurring characters

ValueCountFrequency (%)
032363
99.4%
1198
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032363
99.4%
1198
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032363
99.4%
1198
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032363
99.4%
1198
 
0.6%

country_ Poland
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32501 
1
 
60

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032501
99.8%
160
 
0.2%

Length

2022-06-25T17:54:03.447866image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:54:03.785591image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032501
99.8%
160
 
0.2%

Most occurring characters

ValueCountFrequency (%)
032501
99.8%
160
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032501
99.8%
160
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032501
99.8%
160
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032501
99.8%
160
 
0.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32524 
1
 
37

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032524
99.9%
137
 
0.1%

Length

2022-06-25T17:54:04.147542image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:54:04.637594image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032524
99.9%
137
 
0.1%

Most occurring characters

ValueCountFrequency (%)
032524
99.9%
137
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032524
99.9%
137
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032524
99.9%
137
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032524
99.9%
137
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32447 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032447
99.6%
1114
 
0.4%

Length

2022-06-25T17:54:05.472306image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:54:06.024783image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032447
99.6%
1114
 
0.4%

Most occurring characters

ValueCountFrequency (%)
032447
99.6%
1114
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032447
99.6%
1114
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032447
99.6%
1114
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032447
99.6%
1114
 
0.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32549 
1
 
12

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032549
> 99.9%
112
 
< 0.1%

Length

2022-06-25T17:54:06.459848image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:54:06.991036image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032549
> 99.9%
112
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
032549
> 99.9%
112
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032549
> 99.9%
112
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032549
> 99.9%
112
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032549
> 99.9%
112
 
< 0.1%

country_ South
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32481 
1
 
80

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032481
99.8%
180
 
0.2%

Length

2022-06-25T17:54:07.443139image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:54:07.897494image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032481
99.8%
180
 
0.2%

Most occurring characters

ValueCountFrequency (%)
032481
99.8%
180
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032481
99.8%
180
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032481
99.8%
180
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032481
99.8%
180
 
0.2%

country_ Taiwan
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32510 
1
 
51

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032510
99.8%
151
 
0.2%

Length

2022-06-25T17:54:08.384965image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:54:08.818355image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032510
99.8%
151
 
0.2%

Most occurring characters

ValueCountFrequency (%)
032510
99.8%
151
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032510
99.8%
151
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032510
99.8%
151
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032510
99.8%
151
 
0.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32543 
1
 
18

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032543
99.9%
118
 
0.1%

Length

2022-06-25T17:54:09.168075image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:54:09.718590image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032543
99.9%
118
 
0.1%

Most occurring characters

ValueCountFrequency (%)
032543
99.9%
118
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032543
99.9%
118
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032543
99.9%
118
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032543
99.9%
118
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32542 
1
 
19

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032542
99.9%
119
 
0.1%

Length

2022-06-25T17:54:10.230444image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:54:10.724132image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032542
99.9%
119
 
0.1%

Most occurring characters

ValueCountFrequency (%)
032542
99.9%
119
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032542
99.9%
119
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032542
99.9%
119
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032542
99.9%
119
 
0.1%

country_ United-States
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
1
29170 
0
3391 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
129170
89.6%
03391
 
10.4%

Length

2022-06-25T17:54:11.202177image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:54:11.749343image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
129170
89.6%
03391
 
10.4%

Most occurring characters

ValueCountFrequency (%)
129170
89.6%
03391
 
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
129170
89.6%
03391
 
10.4%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
129170
89.6%
03391
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
129170
89.6%
03391
 
10.4%

country_ Vietnam
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32494 
1
 
67

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032494
99.8%
167
 
0.2%

Length

2022-06-25T17:54:12.194278image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:54:12.701969image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032494
99.8%
167
 
0.2%

Most occurring characters

ValueCountFrequency (%)
032494
99.8%
167
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032494
99.8%
167
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032494
99.8%
167
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032494
99.8%
167
 
0.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size254.5 KiB
0
32545 
1
 
16

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters32561
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
032545
> 99.9%
116
 
< 0.1%

Length

2022-06-25T17:54:13.211233image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-06-25T17:54:13.743121image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
032545
> 99.9%
116
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
032545
> 99.9%
116
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number32561
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032545
> 99.9%
116
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common32561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
032545
> 99.9%
116
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII32561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032545
> 99.9%
116
 
< 0.1%

Interactions

2022-06-25T17:52:19.022242image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:04.267087image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:07.682976image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:10.776375image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:12.950568image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:15.539109image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:19.573386image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:05.048278image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:08.281419image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:11.118436image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:13.531410image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:16.022770image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:20.215794image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:05.574177image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:08.830461image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:11.374251image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:14.018803image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:16.523934image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:20.772782image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:06.071418image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:09.398800image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:11.628017image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:14.672040image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:17.440210image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:21.314758image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:06.630710image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:09.861888image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:11.970491image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:14.998178image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:17.917811image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:21.906615image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:07.150170image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:10.299731image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:12.406624image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:15.209374image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-06-25T17:52:18.462604image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2022-06-25T17:54:14.622255image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-06-25T17:54:18.764754image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-06-25T17:54:22.372552image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-06-25T17:54:26.758919image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-06-25T17:54:30.868934image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-06-25T17:52:24.454155image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

agefnlwgteducation-numcapital-gaincapital-losshours-per-weeksalaryworkclass_ ?workclass_ Federal-govworkclass_ Local-govworkclass_ Never-workedworkclass_ Privateworkclass_ Self-emp-incworkclass_ Self-emp-not-incworkclass_ State-govworkclass_ Without-payeducation_ 10theducation_ 11theducation_ 12theducation_ 1st-4theducation_ 5th-6theducation_ 7th-8theducation_ 9theducation_ Assoc-acdmeducation_ Assoc-voceducation_ Bachelorseducation_ Doctorateeducation_ HS-gradeducation_ Masterseducation_ Preschooleducation_ Prof-schooleducation_ Some-collegemarital-status_ Divorcedmarital-status_ Married-AF-spousemarital-status_ Married-civ-spousemarital-status_ Married-spouse-absentmarital-status_ Never-marriedmarital-status_ Separatedmarital-status_ Widowedoccupation_ ?occupation_ Adm-clericaloccupation_ Armed-Forcesoccupation_ Craft-repairoccupation_ Exec-managerialoccupation_ Farming-fishingoccupation_ Handlers-cleanersoccupation_ Machine-op-inspctoccupation_ Other-serviceoccupation_ Priv-house-servoccupation_ Prof-specialtyoccupation_ Protective-servoccupation_ Salesoccupation_ Tech-supportoccupation_ Transport-movingrelationship_ Husbandrelationship_ Not-in-familyrelationship_ Other-relativerelationship_ Own-childrelationship_ Unmarriedrelationship_ Wiferace_ Amer-Indian-Eskimorace_ Asian-Pac-Islanderrace_ Blackrace_ Otherrace_ Whitesex_ Femalesex_ Malecountry_ ?country_ Cambodiacountry_ Canadacountry_ Chinacountry_ Columbiacountry_ Cubacountry_ Dominican-Republiccountry_ Ecuadorcountry_ El-Salvadorcountry_ Englandcountry_ Francecountry_ Germanycountry_ Greececountry_ Guatemalacountry_ Haiticountry_ Holand-Netherlandscountry_ Hondurascountry_ Hongcountry_ Hungarycountry_ Indiacountry_ Irancountry_ Irelandcountry_ Italycountry_ Jamaicacountry_ Japancountry_ Laoscountry_ Mexicocountry_ Nicaraguacountry_ Outlying-US(Guam-USVI-etc)country_ Perucountry_ Philippinescountry_ Polandcountry_ Portugalcountry_ Puerto-Ricocountry_ Scotlandcountry_ Southcountry_ Taiwancountry_ Thailandcountry_ Trinadad&Tobagocountry_ United-Statescountry_ Vietnamcountry_ Yugoslavia
039775161321740400000000010000000000100000000001000100000000000000100000000101000000000000000000000000000000000000000100
150833111300130000000100000000000100000000100000000100000000001000000000101000000000000000000000000000000000000000100
238215646900400000010000000000000001000010000000000001000000000100000000101000000000000000000000000000000000000000100
353234721700400000010000010000000000000000100000000001000000001000000010001000000000000000000000000000000000000000100
4283384091300400000010000000000000100000000100000000000000100000000010010010000001000000000000000000000000000000000000
5372845821400400000010000000000000000100000100000000100000000000000010000110000000000000000000000000000000000000000100
649160187500160000010000000000100000000000010000000000010000000100000010010000000000000000000000001000000000000000000
752209642900451000000100000000000001000000100000000100000000001000000000101000000000000000000000000000000000000000100
8314578114140840501000010000000000000000100000001000000000000100000100000000110000000000000000000000000000000000000000100
9421594491351780401000010000000000000100000000100000000100000000001000000000101000000000000000000000000000000000000000100

Last rows

agefnlwgteducation-numcapital-gaincapital-losshours-per-weeksalaryworkclass_ ?workclass_ Federal-govworkclass_ Local-govworkclass_ Never-workedworkclass_ Privateworkclass_ Self-emp-incworkclass_ Self-emp-not-incworkclass_ State-govworkclass_ Without-payeducation_ 10theducation_ 11theducation_ 12theducation_ 1st-4theducation_ 5th-6theducation_ 7th-8theducation_ 9theducation_ Assoc-acdmeducation_ Assoc-voceducation_ Bachelorseducation_ Doctorateeducation_ HS-gradeducation_ Masterseducation_ Preschooleducation_ Prof-schooleducation_ Some-collegemarital-status_ Divorcedmarital-status_ Married-AF-spousemarital-status_ Married-civ-spousemarital-status_ Married-spouse-absentmarital-status_ Never-marriedmarital-status_ Separatedmarital-status_ Widowedoccupation_ ?occupation_ Adm-clericaloccupation_ Armed-Forcesoccupation_ Craft-repairoccupation_ Exec-managerialoccupation_ Farming-fishingoccupation_ Handlers-cleanersoccupation_ Machine-op-inspctoccupation_ Other-serviceoccupation_ Priv-house-servoccupation_ Prof-specialtyoccupation_ Protective-servoccupation_ Salesoccupation_ Tech-supportoccupation_ Transport-movingrelationship_ Husbandrelationship_ Not-in-familyrelationship_ Other-relativerelationship_ Own-childrelationship_ Unmarriedrelationship_ Wiferace_ Amer-Indian-Eskimorace_ Asian-Pac-Islanderrace_ Blackrace_ Otherrace_ Whitesex_ Femalesex_ Malecountry_ ?country_ Cambodiacountry_ Canadacountry_ Chinacountry_ Columbiacountry_ Cubacountry_ Dominican-Republiccountry_ Ecuadorcountry_ El-Salvadorcountry_ Englandcountry_ Francecountry_ Germanycountry_ Greececountry_ Guatemalacountry_ Haiticountry_ Holand-Netherlandscountry_ Hondurascountry_ Hongcountry_ Hungarycountry_ Indiacountry_ Irancountry_ Irelandcountry_ Italycountry_ Jamaicacountry_ Japancountry_ Laoscountry_ Mexicocountry_ Nicaraguacountry_ Outlying-US(Guam-USVI-etc)country_ Perucountry_ Philippinescountry_ Polandcountry_ Portugalcountry_ Puerto-Ricocountry_ Scotlandcountry_ Southcountry_ Taiwancountry_ Thailandcountry_ Trinadad&Tobagocountry_ United-Statescountry_ Vietnamcountry_ Yugoslavia
325513234066600400000010000100000000000000000100000000001000000001000001000001000000000000000000000000000000000000000100
3255243846611100450000010000000000001000000000100000000000000001001000000000101000000000000000000000000000000000000000100
32553321161381400110000010000000000000000100000001000000000000000100100000100001000000000000000000000000000000000000100000
32554533218651400401000010000000000000000100000100000000100000000001000000000101000000000000000000000000000000000000000100
32555223101521000400000010000000000000000000100001000000000000010000100000000101000000000000000000000000000000000000000100
32556272573021200380000010000000000010000000000100000000000000000100000010000110000000000000000000000000000000000000000100
3255740154374900401000010000000000000001000000100000000000100000001000000000101000000000000000000000000000000000000000100
3255858151910900400000010000000000000001000000000010100000000000000000100000110000000000000000000000000000000000000000100
3255922201490900200000010000000000000001000000001000100000000000000001000000101000000000000000000000000000000000000000100
32560522879279150240401000001000000000000001000000100000000100000000000000010000110000000000000000000000000000000000000000100

Duplicate rows

Most frequently occurring

agefnlwgteducation-numcapital-gaincapital-losshours-per-weeksalaryworkclass_ ?workclass_ Federal-govworkclass_ Local-govworkclass_ Never-workedworkclass_ Privateworkclass_ Self-emp-incworkclass_ Self-emp-not-incworkclass_ State-govworkclass_ Without-payeducation_ 10theducation_ 11theducation_ 12theducation_ 1st-4theducation_ 5th-6theducation_ 7th-8theducation_ 9theducation_ Assoc-acdmeducation_ Assoc-voceducation_ Bachelorseducation_ Doctorateeducation_ HS-gradeducation_ Masterseducation_ Preschooleducation_ Prof-schooleducation_ Some-collegemarital-status_ Divorcedmarital-status_ Married-AF-spousemarital-status_ Married-civ-spousemarital-status_ Married-spouse-absentmarital-status_ Never-marriedmarital-status_ Separatedmarital-status_ Widowedoccupation_ ?occupation_ Adm-clericaloccupation_ Armed-Forcesoccupation_ Craft-repairoccupation_ Exec-managerialoccupation_ Farming-fishingoccupation_ Handlers-cleanersoccupation_ Machine-op-inspctoccupation_ Other-serviceoccupation_ Priv-house-servoccupation_ Prof-specialtyoccupation_ Protective-servoccupation_ Salesoccupation_ Tech-supportoccupation_ Transport-movingrelationship_ Husbandrelationship_ Not-in-familyrelationship_ Other-relativerelationship_ Own-childrelationship_ Unmarriedrelationship_ Wiferace_ Amer-Indian-Eskimorace_ Asian-Pac-Islanderrace_ Blackrace_ Otherrace_ Whitesex_ Femalesex_ Malecountry_ ?country_ Cambodiacountry_ Canadacountry_ Chinacountry_ Columbiacountry_ Cubacountry_ Dominican-Republiccountry_ Ecuadorcountry_ El-Salvadorcountry_ Englandcountry_ Francecountry_ Germanycountry_ Greececountry_ Guatemalacountry_ Haiticountry_ Holand-Netherlandscountry_ Hondurascountry_ Hongcountry_ Hungarycountry_ Indiacountry_ Irancountry_ Irelandcountry_ Italycountry_ Jamaicacountry_ Japancountry_ Laoscountry_ Mexicocountry_ Nicaraguacountry_ Outlying-US(Guam-USVI-etc)country_ Perucountry_ Philippinescountry_ Polandcountry_ Portugalcountry_ Puerto-Ricocountry_ Scotlandcountry_ Southcountry_ Taiwancountry_ Thailandcountry_ Trinadad&Tobagocountry_ United-Statescountry_ Vietnamcountry_ Yugoslavia# duplicates
8251959942004000000100000001000000000000000010000000000010000001000000001100000000000000100000000000000000000000000003
019972619004000000100000000000000010000000010000000100000000001000000001010000000000000000000000000000000000000001002
11913815310001000000100000000000000000001000010001000000000000000010000001100000000000000000000000000000000000000001002
21914667910003000000100000000000000000001000010000001000000000000010000100010000000000000000000000000000000000000001002
31925157910001400000100000000000000000001000010000000000100000000010000001010000000000000000000000000000000000000001002
42010765810001000000100000000000000000001000010000000000000001001000000001100000000000000000000000000000000000000001002
5212433681005000000100000000000000000100000010000000100000000001000000001010000000000000000000000000010000000000000002
62125005110001000000100000000000000000001000010000000000001000000010000001100000000000000000000000000000000000000001002
7232401373005500000100000000100000000000000010000000010000000001000000001010000000000000000000000000010000000000000002
92530814413004000000100000000000001000000000010000010000000000001000000001010000000000000000000000000010000000000000002